Towards a statistically robust determination of minimum water potential and hydraulic risk in plants

Abstract

Minimum water potential (Ψmin) is a key variable to characterize dehydration tolerance and hydraulic safety margins (HSM) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and by the underlying probability distribution. We compare alternative approaches to estimate Ψmin and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk. Our results show that current estimates of Ψmin and HSM are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψmin estimates between these species and those living under milder conditions are partly artifactual. When this bias is corrected using EVT methods, resulting HSM tend to increase substantially with resistance to embolism across species. Although data availability and representativeness remain the main challenges for proper determination of Ψmin, a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψmin opens new ground for characterizing plant hydraulic risks.